Swiftask indexes and analyzes your Aircall recordings. Ask questions in natural language and get answers based on your past conversations.
Result:
Turn thousands of hours of calls into a goldmine of actionable insights in seconds.
AI Agents
aircall
Connector aircall · Secure OAuth 2.0
Every day, your team exchanges critical information with customers via Aircall. However, this data remains locked in audio files. You cannot search by keyword, and extracting trends is impossible without listening to hours of recordings.
Main negative impacts:
Massive time loss
Finding a customer promise or technical spec requires re-listening to dozens of calls. This is a major productivity drain.
Siloed information
Valuable insights remain isolated in individual calls. It's impossible to correlate recurring issues across the company.
Limited customer reactivity
When speaking to a client, you cannot extract their past needs in real-time. Your support team lacks immediate context.
Swiftask connects your Aircall calls to an AI semantic search engine. You no longer search by date or number, but by concept, question, or topic. The AI finds the exact answer in your recordings.
BEFORE / AFTER
Without Swiftask
A customer calls about a recurring issue. The agent must search the CRM, listen to previous Aircall recordings, take notes, and try to remember past exchanges. The customer waits, the agent is stressed, and the experience suffers.
With Swiftask + Aircall
The agent asks Swiftask: 'What were this customer's pain points in the last 3 calls?'. In seconds, the AI analyzes the Aircall history and provides a precise context summary. The agent responds with immediate expertise.
1
STEP 1 : Connect your Aircall account to Swiftask
Authorize Swiftask to access your Aircall recordings via a secure integration.
2
STEP 2 : Launch AI indexing
Swiftask transcribes and semantically analyzes your past and future calls. No manual action required.
3
STEP 3 : Ask your questions
Use the Swiftask search interface to query your conversations just like a search engine.
4
STEP 4 : Get contextual answers
The AI returns the exact answer, sourced by the audio snippet and the corresponding transcription.
Swiftask analyzes tone, intent, objections, and needs expressed by your customers during Aircall calls.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-aircall@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Cut the time spent searching for information in your call history by 90%.
Understand exactly what your customers think of your products through semantic analysis.
Give your agents all the keys to respond with context and relevance from the start of the call.
Identify trends, bugs, or sales opportunities hidden in your conversations.
Your call data is processed with the highest security standards in the market.
Swiftask applies enterprise-grade security standards for your aircall automations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
| Metric | Before | After |
|---|---|---|
| Information search time | Several minutes per call | A few seconds |
| Support quality | Partial information | Complete and contextual history |
| Actionable insights | None, unprocessed data | Automated voice-based reports |
Turn thousands of hours of calls into a goldmine of actionable insights in seconds.